Flood hazard and risk assessment using GIS and remote sensing in the case of Ziway Lake watershed, central Main Ethiopian Rift

Among the most destructive natural disasters, floods cause more property damage and fatalities than any other natural hazard. This research aimed to identify flood hazard and risk-prone areas in Ziway Lake watershed, which is situated in the central Main Ethiopian Rift, utilizing geospatial technology such as GIS (geographic information system) and remote sensing techniques. Flood hazard zones have been mapped by analyzing eleven significant indicators: Topographic Wetness Index (TWI), elevation, slope, Normalized Difference Vegetation Index (NDVI), drainage density, rainfall, land-use, soil texture, distance from rivers, distance from roads, and lithology. The weightage of each factor was assigned using the Analytical Hierarchy Process (AHP). Three main factors, such as population density, flood hazard, and land-use, have been employed to identify flood risk zones. According to the flood hazard map, 60 % of watersheds (4371 km 2 ) fall within the high to very high-risk zones. The rest are classified as moderate (1995 km 2 or 27 %) and low (906 km 2 or 12 %), while the high and very high categories specifically account for 2328 km 2 (32 %) and 2043 km 2 (28 %), respectively. According to the flood risk map, 2424 km 2 (35 %) of the region is located in areas with high to very high flood risk. Historical flood data verified the model's reliability and accuracy in identifying regions vulnerable to floods. The findings can be valuable tools for decision-makers to guide preventive measures, improve land use planning, and enhance flood risk management. • GIS and Remote Sensing, approaches assess flood hazard and risk areas. • Mapped flood hazard area using eleven thematic layers: EL, SL, DD, DRV, TWI, NFVI, RF, LULC, FRO, ST, and LIT. • Identified flood risk area using three layers: Flood hazard, LULC and population density. • Flood risk map revealed that 35 % of the watershed is under high to very high flood risk. • The resulting can serve as valuable tools for decision-makers in guiding preventive measures.

Authors

Publication Details

Journal
Environmental and Sustainability Indicators
Published
2025-09-12
DOI
https://doi.org/10.1016/j.indic.2025.100920
Citations
4
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
4.42
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Flood hazard and risk assessment using GIS and remote sensing in the case of Ziway Lake watershed, central Main Ethiopian Rift

Tariku Takele, Shankar Karuppannan, Dechasa Diriba, Musa Husein
4 citations
Environmental and Sustainability Indicators
Flood Risk Assessment and Management
4.42
article

Flood hazard and risk assessment using GIS and remote sensing in the case of Ziway Lake watershed, central Main Ethiopian Rift

Tariku Takele, Shankar Karuppannan, Dechasa Diriba, Musa Husein
article en
4 citations

Abstract

Among the most destructive natural disasters, floods cause more property damage and fatalities than any other natural hazard. This research aimed to identify flood hazard and risk-prone areas in Ziway Lake watershed, which is situated in the central Main Ethiopian Rift, utilizing geospatial technology such as GIS (geographic information system) and remote sensing techniques. Flood hazard zones have been mapped by analyzing eleven significant indicators: Topographic Wetness Index (TWI), elevation, slope, Normalized Difference Vegetation Index (NDVI), drainage density, rainfall, land-use, soil texture, distance from rivers, distance from roads, and lithology. The weightage of each factor was assigned using the Analytical Hierarchy Process (AHP). Three main factors, such as population density, flood hazard, and land-use, have been employed to identify flood risk zones. According to the flood hazard map, 60 % of watersheds (4371 km 2 ) fall within the high to very high-risk zones. The rest are classified as moderate (1995 km 2 or 27 %) and low (906 km 2 or 12 %), while the high and very high categories specifically account for 2328 km 2 (32 %) and 2043 km 2 (28 %), respectively. According to the flood risk map, 2424 km 2 (35 %) of the region is located in areas with high to very high flood risk. Historical flood data verified the model's reliability and accuracy in identifying regions vulnerable to floods. The findings can be valuable tools for decision-makers to guide preventive measures, improve land use planning, and enhance flood risk management. • GIS and Remote Sensing, approaches assess flood hazard and risk areas. • Mapped flood hazard area using eleven thematic layers: EL, SL, DD, DRV, TWI, NFVI, RF, LULC, FRO, ST, and LIT. • Identified flood risk area using three layers: Flood hazard, LULC and population density. • Flood risk map revealed that 35 % of the watershed is under high to very high flood risk. • The resulting can serve as valuable tools for decision-makers in guiding preventive measures.

Environmental and Sustainability IndicatorsVol. 28
Openalex Percentile: Top 5%
Flood Risk Assessment and Management
4.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.